… paper is the early diagnosis of lung cancer by examining the … A stratified 10-fold cross-validation
comparative analysis was … with comparative study of classification algorithm for detection …

… reduce the false positive rate and provide high sensitivity in detecting lung cancer. The main
objective of this research is to improve classification accuracy. Researcher achieved 91.23…

… used to classify the presence of lung carcinoma. The motive of this study is to develop
precision and determine specific value for detection of lung carcinoma at an earlier stage using a …

… DISCUSSION In this paper a comparative analysis of different segmentation techniques for
lung cancer detection … are so many techniques developed for the detection of lung cancer. An …

… This study had successfully done the comparative studies for Otsu’s thresholding, watershed
segmentation and k-mean clustering for image segmentation of lung cancer detection. The …

… Abstract: This paper focuses on early stage lung cancer detection. Lung cancer is prominent
cancer … It creates need of detecting the lung nodule at early stage in Computer Tomography …

… several deep neural networks for recognition of pulmonary cancer. In our study, we find that
Convolutional neural networks are used for pulmonary cancer detection in most of the cases, …

… Analysis of concordances and discordances did not indicate whether one modality could
be substituted for the other, or which diagnostic strategy might be more useful. …

… In 2010, a comparative study of six different CAD systems using the same data set, five of
them achieved better detection sensitivity for smaller nodules, the outcome of the present study …

… for non-small cell lung cancer (NSCLC). This study aimed to enhance prediction and detection
using eXtreme Gradient Boosting (XGBoost) model to detect lung cancer diagnoses and …